DocumentCode :
2719787
Title :
A genetic algorithm for the adaptation of service compositions
Author :
Linner, David ; Pfeffer, Heiko ; Steglich, Stephan
Author_Institution :
Tech. Univ. Berlin, Berlin
fYear :
2007
fDate :
10-12 Dec. 2007
Firstpage :
277
Lastpage :
281
Abstract :
The view on applications in large-scale open systems shifted to a service-oriented perspective, where each functional feature forming an application is regarded as service. The services which constitute an application can be physically spread over different network nodes and can be even provided by different administrative entities. According to the vision of the BIONETS project we are additionally facing a dynamically changing computing environment, which entails a dynamically changing set of available services. We investigate how service compositions, on which novel applications are based on, can flexibly be adapted to the changing conditions in the computing environment, while going beyond late-binding mechanisms. We apply methods of genetic programming to modify the structures describing service compositions to find compensation for types of services no longer available to applications. In this paper, we describe the current state of our efforts on complex algorithms for service composition transformation, based on the application of genetic operators to graph based service composition representations.
Keywords :
genetic algorithms; graph theory; large-scale systems; open systems; software architecture; BIONETS project; administrative entities; complex algorithms; computing environment; functional feature forming; genetic algorithm; graph based service composition representations; large-scale open systems; service composition transformation; Availability; Computer vision; Genetic algorithms; Genetic mutations; Genetic programming; Large-scale systems; Open systems; Permission; Service oriented architecture; Web services; Genetic Algorithm; Service Composition; Service-oriented Architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Models of Network, Information and Computing Systems, 2007. Bionetics 2007. 2nd
Conference_Location :
Budapest
Print_ISBN :
978-963-9799-05-9
Electronic_ISBN :
978-963-9799-05-9
Type :
conf
DOI :
10.1109/BIMNICS.2007.4610126
Filename :
4610126
Link To Document :
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